Hospital-Based Medicine

Multimodal Data Matters: Language Model Pre-Training Over Structured and Unstructured Electronic Health Records.

As two important textual modalities in electronic health records (EHR), both structured data (clinical codes) and unstructured data (clinical narratives) have recently been increasingly applied to the healthcare domain. Most existing EHR-oriented studies, however, either focus on a particular modality or integrate data from different modalities in a straightforward manner, which usually treats str...

Quo Vadis, Amadeo Hand Robot? A Randomized Study with a Hand Recovery Predictive Model in Subacute Stroke.

BACKGROUND: Early identification of hand-prognosis-factors at patient's admission could help to select optimal synergistic rehabilitation programs based on conventional (COHT) or robot-assisted (RAT) therapies.

Same-Day Discharge After Robot-Assisted Partial Nephrectomy: Is It Worth It?

Robot-assisted partial nephrectomy (RAPN) has traditionally been performed as an inpatient procedure; however, recent studies have suggested the feas...

Minimally Invasive Management of Post-treatment Rectovesical Fistulae.

The aim of this study is to report our experience in minimally invasive management of rectovesical fistulae (RVFs). Between 2004 and 2021, 24 patien...

Hourly Water Level Forecasting in an Hydroelectric Basin Using Spatial Interpolation and Artificial Intelligence.

In this work, a new hydroelectric basin modelling approach is described and applied to the Pontecosi basin, Italy. Several types of data sources were ...

Predictive analysis of lower limb fractures in the orthopedic complex operative unit using artificial intelligence: the case study of AOU Ruggi.

The length of stay (LOS) in hospital is one of the main parameters for evaluating the management of a health facility, of its departments in relation ...

Acute Intraoperative Hyperkalemia During Robot-Assisted Radical Cystectomy: A Case Report.

A 50-year-old man with muscle-invasive bladder cancer was scheduled for a robotic radical cystectomy. Four hours into the surgery, his electrocardiogr...

Machine learning prediction of academic collaboration networks.

We investigate the different roles played by nodes' network and non-network attributes in explaining the formation of European university collaboratio...

From computer to bedside, involving neonatologists in artificial intelligence models for neonatal medicine.

In recent years, data have become the main driver of medical innovation. With increased availability and decreased price of storage and computing powe...

Use of Robot-Assisted Gait Training in Pediatric Patients with Cerebral Palsy in an Inpatient Setting-A Randomized Controlled Trial.

Robot-assisted gait training (RAGT) provides a task-based support of walking using exoskeletons. Evidence shows moderate, but positive effects in the ...

Cost drivers for benign hysterectomy within a health care system: Influence of patient, perioperative, and hospital factors.

OBJECTIVE: To identify patient, perioperative, and hospital factors that drive total hospital charges for benign hysterectomy.

Robot-assisted rehabilitation training improves knee function and daily activity ability in older adults following total knee arthroplasty.

To evaluate the effects of robot-assisted rehabilitation training on knee function and the daily activity ability of older adults following total knee...

A Machine Learning-Based Approach to Predict Prognosis and Length of Hospital Stay in Adults and Children With Traumatic Brain Injury: Retrospective Cohort Study.

BACKGROUND: The treatment and care of adults and children with traumatic brain injury (TBI) constitute an intractable global health problem. Predictin...

Multitask Deep Learning for Cost-Effective Prediction of Patient's Length of Stay and Readmission State Using Multimodal Physical Activity Sensory Data.

In a hospital, accurate and rapid mortality prediction of Length of Stay (LOS) is essential since it is one of the essential measures in treating pati...

Machine learning and circular bioeconomy: Building new resource efficiency from diverse waste streams.

Biorefinery systems are playing pivotal roles in the technological support of resource efficiency for circular bioeconomy. Meanwhile, artificial intel...

Machine-learning-based risk stratification for probability of dying in patients with basal ganglia hemorrhage.

To confirm whether machine learning algorithms (MLA) can achieve an effective risk stratification of dying within 7 days after basal ganglia hemorrhag...

Neurosurgery inpatient outcome prediction for discharge planning with deep learning and transfer learning.

INTRODUCTION: Deep learning may be able to assist with the prediction of neurosurgical inpatient outcomes. The aims of this study were to investigate ...

Developing a deep learning natural language processing algorithm for automated reporting of adverse drug reactions.

The detection of adverse drug reactions (ADRs) is critical to our understanding of the safety and risk-benefit profile of medications. With an inciden...

Robotic-assisted spine surgery allows for increased pedicle screw sizes while still improving safety as indicated by elevated triggered electromyographic thresholds.

The present study used triggered electromyographic (EMG) testing as a tool to determine the safety of pedicle screw placement. In this Institutional R...

Efficacy and Safety of the "Trisection Method" Training System for Robot-Assisted Radical Cystectomy at a Single Institution in Japan.

To maintain a surgeon's concentration, reduce fatigue, and train young surgeons, surgical procedures for bladder cancer are divided into the following...